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A model for assessing maturity of hydrogen supply chain resilience: a complexity-inspired approach

Liang Kong et al.

International Journal of Production Research2026https://doi.org/10.1080/00207543.2026.2623533article
AJG 3ABDC A
Weight
0.41

Abstract

This study presents a maturity model (MM) for supply chain resilience management (SCRM) in the hydrogen sector, aimed at identifying resilience gaps and guiding improvements. The model is developed using an iterative approach combining literature review, expert interviews, and case studies. Grounded in design science research and complex adaptive systems (CAS) theory, the MM supports building adaptable, scalable supply chains that can manage regulatory shifts and industry transitions. Case study findings reveal that the development of SCRM maturity in the upstream hydrogen sector is constrained by downstream uncertainties and fragmented market mechanisms. Vertical integration across the supply chain significantly enhances hydrogen supply chain resilience. The MM offers a structured approach for hydrogen companies to improve response capabilities and apply scalable, strategy-aligned resilience measures. Theoretically, it advances understanding of CAS dynamics in SCRM. Practically, it provides managers with actionable guidance for implementing resilience strategies across the industry.

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https://doi.org/https://doi.org/10.1080/00207543.2026.2623533

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@article{liang2026,
  title        = {{A model for assessing maturity of hydrogen supply chain resilience: a complexity-inspired approach}},
  author       = {Liang Kong et al.},
  journal      = {International Journal of Production Research},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1080/00207543.2026.2623533},
}

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A model for assessing maturity of hydrogen supply chain resilience: a complexity-inspired approach

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Evidence weight

0.41

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.